Activity: Participating in or organising an event types › Participation in conference
Data-Driven Diagnosis: Using R to Advance Kidney Disease Research
Kidney disease affects around 850 million people globally, with this number set to rise; by 2040, this disease is predicted to become the 5th leading cause of death worldwide. It significantly impacts both patients and their families, with disease progression resulting in the need for dialysis or transplant. To better understand this disease, multiple variables have been studied, such as DNA sequence (genomics), DNA modifications (epigenomics), RNA levels (transcriptomics), environmental factors, and clinical status (electronic healthcare records). In this talk, I described how statistical analysis of these datasets, alongside the utilisation of the NI kidney transplant database, curated over the last five decades, has revealed variation associated with kidney disease. I demonstrated how harnessing R, with packages such as ViSEAGO and Mendelian Randomisation, can highlight the molecular pathways and risk factors associated with these variations. This analysis improves our understanding of the biological processes which may be disrupted during this disease. Moreover, it provides potential targets for early diagnosis of kidney disease, as well as opportunities to develop personalised treatments, ultimately improving patient outcomes.